The tip of the iceberg: A call to embrace anti-localizationism in human neuroscience research

Abstract

Human neuroscience research remains largely preoccupied with mapping distinct brain areas to complex psychological processes and features of mental health disorders. While this reductionist and localizationist perspective has resulted in several substantive contributions to the field, it has long been viewed as only a piece of the puzzle. Emerging evidence now empirically demonstrates how a historical reliance on localizationist techniques may underlie recent challenges to reproducibility and translation in human neuroscience. To advance discovery, we must collectively better incorporate complex systems and machine learning approaches that better capture the multidimensional, dynamic, and interacting nature of the brain. Moreover, we must begin to contend with how to best integrate complementary modalities beyond the brain to better understand complex mental processes.

Neural interactions in the human frontal cortex dissociate reward and punishment learning

“…To address this issue, we repose on recent literature proposing that learning reflects a network phenomenon emerging from neural interactions distributed over cortical-subcortical circuits ( Bassett and Mattar, 2017 ; Hunt and Hayden, 2017 ; Averbeck and Murray, 2020 ; Averbeck and O’Doherty, 2022 ). Indeed, cognitive functions emerge from the dynamic coordination over large-scale and hierarchically organized networks ( Varela et al, 2001 ; Bressler and Menon, 2010 ; Reid et al, 2019 ; Panzeri et al, 2022 ; Thiebaut de Schotten and Forkel, 2022 ; Miller et al, 2024 ; Noble et al, 2024 ) and accumulating evidence supports that information about task variables is widely distributed across brain circuits, rather than anatomically localized ( Parras et al, 2017 ; Saleem et al, 2018 ; Steinmetz et al, 2019 ; Urai et al, 2022 ; Voitov and Mrsic-Flogel, 2022 ).…”